Hedging risks associated with variable priced orders for derivative financial products

ABSTRACT

Systems and methods are provided for executing a hedge transaction in connection with the execution of a derivative product order in which the price of the derivative product is defined by one or more variables. The hedge transaction may be executed at an exchange or match engine that is different from the exchange or match engine executing the derivative product order. The execution of derivative product transaction may be contingent on the existence of an appropriate hedge transaction. Alternatively, a best efforts approach may be used to fill the hedge transaction order after executing the derivative product transaction.

The present application is a continuation of U.S. patent applicationSer. No. 12/966,467, filed Dec. 13, 2010, which is a continuation ofU.S. patent application Ser. No. 12/688,467, filed Jan. 15, 2010, whichis a continuation of U.S. patent application Ser. No. 11/953,650, filedDec. 10, 2007, which is a continuation of U.S. patent application Ser.No. 10/611,458, filed Jul. 1, 2003, which is a continuation-in-part ofU.S. patent application Ser. No. 10/385,152, filed Mar. 10, 2003, theentire disclosures of which are hereby incorporated by reference.

FIELD OF THE INVENTION

The present invention relates to derivative product trading methods andsystems and, in particular, to methods and systems that utilize avariable defined order price and a hedge transaction.

DESCRIPTION OF THE RELATED ART

Computer systems and networks increasingly are being used to tradesecurities and derivatives. Computer systems and networks provideseveral advantages when compared to manual methods of trading. Suchadvantages include increased accuracy, reduced labor costs and theability to quickly disseminate market information.

Options are frequently traded via computer systems and methods. Anoption may be used to hedge risks by allowing parties to agree on aprice for a purchase or sale of another instrument that will take placeat a later time. One type of option is a call option. A call optiongives the purchaser of the option the right, but not the obligation, tobuy a particular asset either at or before a specified later time at aguaranteed price. The guaranteed price is sometimes referred to as thestrike or exercise price. Another type of option is a put option. A putoption gives the purchaser of the option the right, but not theobligation, to sell a particular asset at a later time at the strikeprice. In either instance, the seller of the call or put option can beobligated to perform the associated transactions if the purchaserchooses to exercise its option or upon the expiration of the option.

Traders typically use theoretical models to determine the prices atwhich they will offer to buy and sell options. The theoretical optionpricing models often produce values that reflect an option's sensitivityto changes in predefined variables. These predefined variables areassigned Greek letters, such as delta, gamma, theta, and vega. Delta isa measure of the rate of change in an option's theoretical value for aone-unit change in the price of the option's underlying contract. Thus,delta is the theoretical amount by which the option price can beexpected to change for a change in the price of the underlying contract.As such, delta provides a local measure of the equivalent position riskof an option position with respect to a position in the underlyingcontract. A “50 Delta” option should change its price 50/100, or ½ apoint, for a one point move in its underlying contract.

Gamma is a measure of the rate of change in an option's delta for aone-unit change in the price of the underlying contract. Gamma expresseshow much the option's delta should theoretically change for a one-unitchange in the price of the underlying contract. Theta is a measure ofthe rate of change in an option's theoretical value for a one-unitchange in time to the option's expiration date. Vega is a measure of therate of change in an option's theoretical value for a one-unit change inthe volatility of the underlying contract. Delta, gamma, and vega arethe primary risk management measures used by those who trade in options.

A single option order typically identifies the underlying security, theexpiration date, whether the option is a call or a put, the strike priceand all other standard order terms (e.g. buy/sell, quantity, accountnumber etc.). Each time the price of the underlying contract changes orone of the variables in the trader's theoretical model changes, a tradermay cancel all of the relevant orders, recalculate new order prices andtransmit new order prices to the exchange.

It is common for traders of options contracts to hedge risks bypurchasing underlying futures contracts. In a pit-traded environment,after executing an options transaction, the trader would typically turnto the futures pit and attempt to execute a hedge transaction. Forexample, after purchasing 50 call options contracts of eurodollars witha 50 delta strike, the trader would seek to purchase 25 eurodollarfutures contracts.

Existing trading systems methods do not allow traders to purchasederivative products, such as options, by providing a variable definedderivative product order price. Such systems also do not allow tradersto identify a hedge transaction to be automatically submitted when thederivative product order is filled.

Therefore, there is a need in the art for improved derivative producttrading methods and systems that allow traders to use variable definedderivative product order prices and identify corresponding hedgetransactions.

SUMMARY OF THE INVENTION

The present invention overcomes the problems and limitations of theprior art by providing methods and systems that utilize a variabledefined derivative product order price. Derivative products includeoptions on futures contracts, futures contracts that are functions of orrelate to other futures contracts, or other financial instruments thathave their price related to or derived from an underlying product. Thevariable defined derivative product order price may be in the form of amodel used to price options. When one of the variables of the modelchanges, an exchange computer system may recalculate the derivativeproduct's price without requiring the trader to transmit additional ordifferent information to the computer system.

The derivative product order may also identify one or more correspondinghedge transactions or include information that may be used to identify ahedge transaction. The execution of the derivative product order may becontingent on the availability of a hedge transaction. Alternatively, abest efforts approach may be used to fill a hedge transaction orderafter the execution of the derivative product order.

In one embodiment, advantages of aspects of the present invention areprovided by a method of executing a variable priced derivative productorder that is contingent on the existence of a corresponding hedgetransaction. The method includes receiving at a match system a variablepriced order for a derivative product. The variable priced order mayinclude a derivative product identifier, an underlying productidentifier and at least one price determination variable. Next, apotential derivative product transaction is identified and a search fora hedge product transaction that corresponds to the potential derivativeproduct transaction is conducted. The derivative product transaction isexecuted only when a hedge transaction is available.

In another embodiment, advantages of aspects of the present inventionare provided by a method of hedging risks associated with the purchaseof a variable priced derivative product. The method includes executing,at a match system, a variable priced derivative product order. Orderrisk data is received from an order risk management module. Next, a bestefforts approach is used to locate a potential hedge transaction thatcorresponds to the derivative product order. Data of the potential hedgetransaction is compared to the order risk data. In one implementation,the potential hedge transaction is executed when the order risk data isnot exceeded. In other implementations, the potential hedge transactionis executed as long as the order risk data is not exceeded prior to thehedge transaction. In still other implementations, a portion of thehedge transaction is cancelled to prevent exceeding the order risk data.

In other embodiments, the present invention can be partially or whollyimplemented on a computer-readable medium, for example, by storingcomputer-executable instructions or modules, or by utilizingcomputer-readable data structures.

Of course, the methods and systems of the above-referenced embodimentsmay also include other additional elements, steps, computer-executableinstructions, or computer-readable data structures. In this regard,other embodiments are disclosed and claimed herein as well.

The details of these and other embodiments of the present invention areset forth in the accompanying drawings and the description below. Otherfeatures and advantages of the invention will be apparent from thedescription and drawings, and from the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention may take physical form in certain parts and steps,embodiments of which will be described in detail in the followingdescription and illustrated in the accompanying drawings that form apart hereof, wherein:

FIG. 1 shows a computer network system that may be used to implementaspects of the present invention;

FIG. 2 illustrates a system in which traders exchange information with amatch system, in accordance with an embodiment of the invention;

FIG. 3 illustrates a variable defined derivative product order inaccordance with an embodiment of the invention;

FIG. 4 illustrates a computer implemented method of trading a derivativeproduct contract that involves the use of a variable order price, inaccordance with an embodiment of the invention;

FIG. 5 illustrates a method of processing variable defined derivativeproduct orders by an exchange computer, in accordance with an embodimentof the invention, when the variable defined derivative product orders donot include the identification of hedge transactions;

FIG. 6 illustrates a method of processing variable defined derivativeproduct orders that are contingent on the existence of hedgetransactions, in accordance with an embodiment of the invention;

FIG. 7 illustrates a method of processing variable defined derivativeproduct orders that require a best efforts approach to finding hedgetransactions, in accordance with an embodiment of the invention; and

FIG. 8 illustrates a method of synthetically matching unresolved hedgetransaction orders for orders belonging to a common class, in accordancewith an embodiment of the invention.

DETAILED DESCRIPTION OF THE INVENTION

Aspects of the present invention are preferably implemented withcomputer devices and computer networks that allow users to exchangetrading information. An exemplary trading network environment forimplementing trading systems and methods is shown in FIG. 1. An exchangecomputer system 100 receives orders and transmits market data related toorders and trades to users. Exchange computer system 100 may beimplemented with one or more mainframe, desktop or other computers. Auser database 102 includes information identifying traders and otherusers of exchange computer system 100. Data may include user names andpasswords potentially with other information to identify users uniquelyor collectively. An account data module 104 may process accountinformation that may be used during trades. A match engine module 106 isincluded to match bid and offer prices. Match engine module 106 may beimplemented with software that executes one or more algorithms formatching bids and offers. A trade database 108 may be included to storeinformation identifying trades and descriptions of trades. Inparticular, a trade database may store information identifying the timethat a trade took place and the contract price. An order book module 110may be included to compute or otherwise determine current bid and offerprices. A market data module 112 may be included to collect market dataand prepare the data for transmission to users. A risk management module134 may be included to compute and determine a user's risk utilizationin relation to the user's defined risk thresholds. An order processingmodule 136 may be included to decompose variable defined derivativeproduct and aggregate order types for processing by order book module110 and match engine module 106.)

The trading network environment shown in FIG. 1 includes computerdevices 114, 116, 118, 120 and 122. Each computer device includes acentral processor that controls the overall operation of the computerand a system bus that connects the central processor to one or moreconventional components, such as a network card or modem. Each computerdevice may also include a variety of interface units and drives forreading and writing data or files. Depending on the type of computerdevice, a user can interact with the computer with a keyboard, pointingdevice, microphone, pen device or other input device.

Computer device 114 is shown directly connected to exchange computersystem 100. Exchange computer system 100 and computer device 114 may beconnected via a T1 line, a common local area network (LAN) or othermechanism for connecting computer devices. Computer device 114 is shownconnected to a radio 132. The user of radio 132 may be a trader orexchange employee. The radio user may transmit order or otherinformation to a user of computer device 114. The user of computerdevice 114 may then transmit the trade or other information to exchangecomputer system 100.

Computer devices 116 and 118 are coupled to a LAN 124. LAN 124 may haveone or more of the well-known LAN topologies and may use a variety ofdifferent protocols, such as Ethernet. Computers 116 and 118 maycommunicate with each other and other computers and devices connected toLAN 124. Computers and other devices may be connected to LAN 124 viatwisted pair wires, coaxial cable, fiber optics or other media.Alternatively, a wireless personal digital assistant device (PDA) 122may communicate with LAN 124 or the Internet 126 via radio waves. PDA122 may also communicate with exchange computer system 100 via aconventional wireless hub 128. As used herein, a PDA includes mobiletelephones and other wireless devices that communicate with a networkvia radio waves.

FIG. 1 also shows LAN 124 connected to the Internet 126. LAN 124 mayinclude a router to connect LAN 124 to the Internet 126. Computer device120 is shown connected directly to the Internet 126. The connection maybe via a modem, DSL line, satellite dish or any other device forconnecting a computer device to the Internet.

One or more market makers 130 may maintain a market by providing bid andoffer prices for a derivative or security to exchange computer system100. Exchange computer system 100 may also exchange information withother trade engines, such as trade engine 138. One skilled in the artwill appreciate that numerous additional computers and systems may becoupled to exchange computer system 100. Such computers and systems mayinclude clearing, regulatory and fee systems. Coupling can be direct asdescribed or any other method described herein.

The operations of computer devices and systems shown in FIG. 1 may becontrolled by computer-executable instructions stored oncomputer-readable medium. For example, computer device 116 may includecomputer-executable instructions for receiving order information from auser and transmitting that order information to exchange computer system100. In another example, computer device 118 may includecomputer-executable instructions for receiving market data from exchangecomputer system 100 and displaying that information to a user.

Of course, numerous additional servers, computers, handheld devices,personal digital assistants, telephones and other devices may also beconnected to exchange computer system 100. Moreover, one skilled in theart will appreciate that the topology shown in FIG. 1 is merely anexample and that the components shown in FIG. 1 may be connected bynumerous alternative topologies.

FIG. 2 illustrates a system in which traders 202 and 204 exchangeinformation with a match system 206, in accordance with an embodiment ofthe invention. Trader 202 is shown transmitting a variable definedderivative product order 208 and a limit data 210 to match system 206.Variable defined derivative product order 208 includes theidentification of a derivative product and a variable order price.Variable defined derivative product orders are described in greaterdetail below in connection with FIG. 3. Limit data 210 may act as athrottle to limit the number of transactions entered into by trader 202.Limited data is also described in greater detail below. Trader 204transmits derivative product orders 212 and 216 to match system 206.Each trader may transmit several derivative product orders and mayassociate limit data with one or more of the derivative product orders.As shown in order 212, one or more of the orders may include theidentification of a hedge transaction.

Match system 206 may include several modules for determining prices,matching orders and executing transactions. An order book module 218 maybe included to maintain a listing of current bid and offer prices. Aprice calculation module 220 calculates order prices based on pricedetermination variables provided as part of variable defined derivativeproduct orders. Price calculation module 220 may also calculate orderprices based on formulas received from traders. For example, derivativeproduct order 208 may include a formula that is a function of anunderlying contract, delta and gamma Price calculation module 220 may beconfigured to calculate an order price every time the price of theunderlying contract changes.

Price calculation module 220 may use a default formula with pricedetermination variable values supplied by a trader. In one embodiment,the change in a derivative product price is equal to a second orderTaylor series expansion, such as:ChgUnderlyingPrice*delta+(½(ChgUnderlyingPrice^2*gamma))  (1)wherein ChgUnderlyingPrice is the change in the underlying price. Atrader would supply price determination variables delta and gamma andprice calculation module would track the derivative product price as theunderlying contract changes.

An order risk management module 222 may be included to act as a limitfor the user's exposure for a given risk variable as defined by theuser. For example, trader 202 provided maximum and minimum delta, gammaand vega values to match system 206. Those values may be stored in orderrisk management module 222 and computed before executing transactions.Depending on the user's order types and risk utilization for a givenrisk variable, the user's resting orders for a particular contract maybe auto canceled by match system 206 so that the user is no longer atrisk to exceed their limits. In addition, and depending on the user'sorder type and risk utilization for a given risk variable, the user'sability to enter a buy or sell order may be prohibited should theexecution of that order cause the user to exceed their particular orderrisk management limit. Order risk module may be used to limit a user'sexposure during the processing of derivative product orders and/or hedgetransaction orders.

A formula database 224 may be included to store derivative product orderformulas. The formulas may be provided by traders or may be standardformulas provided by an exchange. A market data module 226 may be usedto collect and disseminate market data. A match engine module 228matches bid and offer prices. Match engine module 228 may be implementedwith software that executes one or more algorithms for matching bids andoffers.

A hedge module 230 may be included to perform hedge transactions basedon derivative product transactions. In one embodiment of the invention,hedge module 230 conducts transactions with a trading engine or matchsystem other than match system 206. Hedge module 230 may also performsome or all of the function of risk management module 134 (shown in FIG.1). Exemplary hedge transactions are described in detail below withreferences to FIGS. 6 and 7.

An order processing module 236 may be included to decompose delta basedand bulk order types for processing by order book module 218 and matchengine module 228. A controller 232 may be included to control theoverall operation of the components shown coupled to bus 234. Controller232 may be implemented with a central processing unit. Match system 206may include modules that perform some or all of the functions of themodules shown in FIG. 1. Moreover, match system 206 may also be coupledto some or all of the elements shown in FIG. 1.

FIG. 3 illustrates a variable defined derivative product order 300 inaccordance with an embodiment of the invention. Variable definedderivative product order 300 may include a field 302 for identifying atrader's account number. The underlying contract may be identified infield 304. The expiration month of the derivative product order may beidentified in field 306. The order may be identified as a put or a callin field 308 and whether the order is a buy or sell in field 310. Thequantity may be identified in field 312 and the strike price may beidentified in field 314. Delta, gamma, and vega values may be identifiedin fields 316, 318 and 320 respectively. Of course, other pricedetermination variables may also be identified as part of a standardvariable defined derivative product order.

A hedge transaction may be identified in field 322. The user may chooseto make the derivative product order contingent on the existence of anavailable hedge transaction by selecting radio button 324. The user mayalso choose to use best efforts to fill the hedge order after theexecution of the derivative product order by selecting radio button 326.

The formula for calculating the price of variable defined derivativeproduct order is identified in field 328. The trader can select astandard formula 330 to compute their derivative product price or selecta custom formula 332. In one embodiment, a standard formula is suppliedby or sponsored by an exchange. When a custom formula is selected, thetrader may also provide a formula in field 334 and the variables infield 336. In one implementation of the invention, variable definedderivative product order 300 is created in the form of an XML for HTMLdocument created by one of the computer devices shown in FIG. 1.Variable defined derivative product order 300 may be encrypted beforebeing transmitted to an exchange. Of course one or more additional oralternative fields may be included. For example, a reference price maybe included to protect against in flight conditions when the referenceprice changes while variable defined derivative product order 300 is intransit.

FIG. 4 illustrates a computer-implemented method of trading a derivativeproduct contract that involves the use of a variable order price, inaccordance with an embodiment of the invention. First, in step 402 it isdetermined whether the trader desires to use a standard exchangesponsored formula. When the trader uses a custom formula, the formula istransmitted to the exchange computer in step 404. Step 404 may alsoinclude the trader or exchange transmitting the formula to other marketparticipants. In step 406, the trader transmits price determinationvariable values for the standard formula to an exchange computer. Forexample, step 406 may include transmitting delta and gamma values to anexchange computer. In step 408 the trader receives underlying data. Theunderlying data may include current bid and offer prices for underlyingput and call futures contracts.

In step 410 it is determined whether the underlying data has changed.The price of an underlying contract may change multiple times persecond. When the underlying contract data has changed, in step 412 thetrader's computer device may recalculate the order price of their deltabased order and all other delta based orders from other users based oncurrent data. In step 414, it is determined whether any of the pricedetermination variables used in the formula to calculate the order pricehave changed. The price determination variables may include delta,gamma, and vega. When the price determination variables have changed, instep 412, the order price is recalculated. Of course, step 412 may beperformed based on changes in current underlying contract data andvariables. The order price may be displayed to the trader or plotted ona graph that tracks order prices.

Some of the advantages of aspects of the present invention are that theyallow traders to maintain an order book and limit the amount ofinformation that must be disseminated by an exchange computer or matchsystem. In particular, an exchange computer or match system may transmita plurality of variable defined derivative product orders to severaldifferent traders only when other derivative product order usersestablish their initial positions. Thereafter, the exchange computer maythen only transmit underlying data or other data used to calculatevariable defined derivative product order prices. Each trader computermay then periodically calculate current order prices based oninformation received from the exchange computer. For example, in step416 it is determined whether other variable defined derivative productorders are received. When variable defined derivative product orders arereceived, in step 418 the trader computer may calculate new order booklistings for current bids and offers related to variable definedderivative product based orders. The order book may be displayed to thetrader in any one of a variety of conventional formats. After step 418,control returns to step 408.

FIG. 5 illustrates a method of processing variable defined derivativeproduct orders by an exchange computer, in accordance with an embodimentof the invention, when the variable defined derivative product orders donot include the identification of hedge transactions. First, in step 502the exchange computer receives variable defined derivative productorders. As described above, the variable defined derivative productorders may be in the form of one or more formulas containing one or moreprice determination variables. In step 504, the exchange computer mayreceive order risk management information to limit the trader's exposurefor a particular risk variable as given by the trader. Next, theexchange computer may receive or otherwise produce market data in step506. The market data may include current underlying prices that may beused to calculate variable defined derivative product order prices. Instep 508, bid and offer prices are calculated. The calculations may bebased on a combination of formulas and variables provided by tradersand/or the exchange. In step 510 the exchange computer finds a matchingbid and offer. A matching bid and offer may be found by match engine228. Before executing a transaction, in step 512 it is determinedwhether one or more order risk management limits provided by the traderhave been exceeded. When a limit has been reached, all outstandingorders that contribute to the risk limit being exceeded further areautomatically cancelled by the computer system in step 514. When thelimits have not been exceeded, in step 516 the derivative producttransaction is executed. Of course, an exchange computer may beconfigured to repeat the method shown in FIG. 5 several times.

FIG. 6 illustrates a method of processing variable defined derivativeproduct orders that are contingent on the existence of hedgetransactions, in accordance with an embodiment of the invention. First,in step 602 a variable defined derivative product order is received. Theorder received in step 602 is preferably received at a match system andmay identify a hedge product transaction. Next, a potential derivativeproduct transaction is identified in step 604. Step 604 may includecalculating a price of the derivative product order using aspects of theinvention described above. Step 606 includes searching for acorresponding hedge product transaction. The hedge product transactionis one that hedges against the risks associated with the variabledefined derivative product transaction. In one embodiment of theinvention, step 606 includes searching for the hedge product transactionin the same match system as a match system used for the derivativeproduct transaction. The use of the same match system facilitateslocking in both the hedge product transaction and the derivative producttransaction before execution of either transaction. In an alternativeembodiment, the search for hedge product transaction takes place in adifferent match system.

Next, in step 608 it is determined whether the hedge product transactionis available. Step 608 may include determining whether the hedge producttransaction satisfies predetermining criteria provided by the user ormatch system. When the hedge transaction is not available, in step 610the derivative product execution does not occur and the process ends.When the hedge product transaction is available, in step 612 thederivative product transaction and hedge product transaction are bothexecuted. The hedge transaction and the hedge product transaction may belocked in and executed by the same match system.

FIG. 7 illustrates a method of processing variable defined derivativeproduct orders that require a best efforts approach to finding hedgetransactions, in accordance with an embodiment of the invention. First,in step 702 a match system receives a variable defined derivativeproduct order. The derivative product order may identify a hedge producttransaction. Next, in step 704 the derivative product transaction isexecuted. Step 704 may include aspects of the invention described above.In particular, the execution of the derivative product transaction mayinclude calculating a variable defined derivative product order price.

In step 706 the match system receives order risk data from an order riskmanagement module, such as order risk management module 222 shown inFIG. 2. The order risk data may include maximum and/or minimum deltaand/or gamma values, described above. Next, in step 708 a best effortsapproach is used to locate a potential hedge product transaction. Thepotential hedge transaction may comprise the fill or kill transaction.In one alternative embodiment, that transaction may comprise a fill andkill transaction. Next, in step 710 it is determined whether the orderrisk data has been exceeded. Step 710 may include comparing the orderrisk data received in step 706 to data relating to the potential hedgetransaction. When the order risk data would be exceeded, all of theuser's risk increasing orders are canceled and the process ends in step712. When the order risk data would not be exceeded, in step 714 thehedge product transaction is executed.

The method shown in FIG. 7 illustrates one exemplary method in which apotential hedge transaction will not be executed if the potentialtransaction would cause the risk data to be exceeded. In otherembodiments, only a portion of the potential hedge transaction isexecuted. For example, if the potential hedge transaction involves 100contracts and the 52^(nd) contract would cause the risk data to beexceeded, a match system would execute a trade for either 51 or 52contracts. In another alternative embodiment, the match system willexecute the entire potential hedge transaction as long as the risk datais not exceeded just prior to execution of the potential hedgetransaction, regardless of whether risk data will be exceeded after thetransaction.

A trader may buy or sell several variable defined derivative productcontracts in a common class and have a need for multiple hedgetransactions. FIG. 8 illustrates a method of synthetically matchingunresolved hedge transaction orders for orders belonging to a commonclass. First in step 802, unresolved hedge transaction orders having apositive value of an order risk variable are prioritized. The prioritymay be based on the magnitudes of the order risk variable. As describedabove, one order risk variable is delta. In step 804 the unresolvedhedge transaction orders having a negative value of the order riskvariable are prioritized. Next, in step 806 the unresolved hedgetransaction orders are synthetically matched according to the prioritiesidentified in steps 802 and 804.

After the synthetic matching, in step 808 it is determined whether anyresidual unresolved hedge transactions exist. When none exist, theprocess ends in step 810. When one or more residual unresolved hedgetransactions exist, a potential hedge transaction is located in step812. Next, in step 814 it is determined whether the execution of thepotential hedge transaction would violate an order risk data rule. Ofcourse step 814 may include determining whether or not the potentialhedge transaction would violate more than one order risk data rule.Exemplary order risk data rules have been described above. When the rulewould be violated, the process ends in step 810. When the rule would notbe violated, the potential hedge transaction is executed in step 816.

The present invention has been described herein with reference tospecific exemplary embodiments thereof. It will be apparent to thoseskilled in the art, that a person understanding this invention mayconceive of changes or other embodiments or variations, which utilizethe principles of this invention without departing from the broaderspirit and scope of the invention as set forth in the appended claims.All are considered within the sphere, spirit, and scope of theinvention. For example, while aspects of the present invention have beendescribed in connection with the trading of derivative products, inother embodiments, aspects of the invention may be used in connectionwith the trading of securities, such as debt, foreign exchange, andequity contracts, and other instruments for which options or otherderivative instruments are traded. Moreover, aspects of the inventionmay be used with over the counter market transactions. Hedgetransactions may include over the counter trades or exchange tradedcontracts. One example of an over the counter trade is a forwardcontract.

1. A method of processing orders, the method comprising: (a) receivingat a match system a variable priced order for a derivative product, thevariable priced order including a variable price and a formula foradjusting the variable price as a function of a change in a price for anunderlying product; (b) identifying a hedge transaction corresponding tothe order for the derivative product; (c) comparing the hedgetransaction to order risk data; and (d) executing at an exchange thehedge transaction and the derivative product order if the order riskdata is not exceeded.
 2. The method of claim 1, further comprisingapplying the formula at the exchange to adjust the variable price as afunction of changes in a price for the underlying product.
 3. The methodof claim 2, further comprising applying the formula at the exchange toadjust the variable price using at least one price determinationvariable value.
 4. The method of claim 1, where the order risk datacomprises a value of delta.
 5. The method of claim 4, where the orderrisk data comprises a value of gamma.
 6. The method of claim 1, wherethe derivative product comprises an options contract and the hedgetransaction comprises a futures contract.
 7. The method of claim 1,where the hedge transaction comprises a fill or kill transaction.
 8. Themethod of claim 1, where the hedge transaction comprises a fill and killtransaction.
 9. The method of claim 1, wherein (d) comprises: executinga maximum number of orders for hedge products that will cause the orderrisk data not to be exceeded.
 10. The method of claim 1, wherein (d)comprises: executing a minimum number of orders for hedge products thatwill cause the order risk data to be exceeded.
 11. The method of claim1, wherein the order risk data comprises a maximum delta value.
 12. Themethod of claim 1, wherein the order risk data comprises a minimum deltavalue.
 13. The method of claim 1, wherein the order risk data comprisesa maximum gamma value.
 14. The method of claim 1, wherein the order riskdata comprises a minimum gamma value.
 15. A match engine configured toprocess orders, the match engine comprising: a processor; a memorycontaining computer executable instructions for causing the processor toperform the steps comprising: (a) receiving a variable priced order fora derivative product, the variable priced order including a variableprice and a formula for adjusting the variable price as a function of achange in a price for an underlying product; (b) identifying a hedgetransaction corresponding to the order for the derivative product; (c)comparing the hedge transaction to order risk data; and (d) executingthe hedge transaction and the derivative product order if the order riskdata is not exceeded.
 16. The match engine of claim 15, wherein theorder risk data comprises a maximum delta value.
 17. The match engine ofclaim 15, wherein the order risk data comprises a minimum delta value.18. The match engine of claim 15, wherein the order risk data comprisesa maximum gamma value.
 19. The match engine of claim 15, wherein theorder risk data comprises a minimum gamma value.
 20. The match engine ofclaim 15, where the hedge transaction comprises a fill or killtransaction.